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Articles Published Processes
3/21/2020 2:52:58 AM | Browse: 901 | Download: 1677
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Received |
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2019-10-13 14:57 |
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Peer-Review Started |
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2019-10-12 04:38 |
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To Make the First Decision |
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Return for Revision |
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2020-01-13 18:36 |
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Revised |
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2020-02-18 15:57 |
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Second Decision |
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2020-02-20 10:19 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2020-02-21 06:07 |
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Articles in Press |
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2020-02-21 06:07 |
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Publication Fee Transferred |
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Edit the Manuscript by Language Editor |
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2020-03-04 22:22 |
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Typeset the Manuscript |
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2020-03-18 01:47 |
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Publish the Manuscript Online |
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2020-03-21 02:52 |
| ISSN |
1007-9327 (print) and 2219-2840 (online) |
| Open Access |
This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ |
| Copyright |
© The Author(s) 2020. Published by Baishideng Publishing Group Inc. All rights reserved. |
| Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
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| Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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| Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
| Website |
http://www.wjgnet.com |
| Category |
Engineering, Biomedical |
| Manuscript Type |
Retrospective Study |
| Article Title |
Radiomics model based on preoperative gadoxetic acid-enhanced MRI for predicting liver failure
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| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Wang-Shu Zhu, Si-Ya Shi, Ze-Hong Yang, Chao Song and Jun Shen |
| ORCID |
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| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| the Guangdong Province Universities and Colleges Pearl River Scholar Funded Scheme (2017) |
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| the Guangdong Natural Science Foundation |
2017A030313777 |
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| Corresponding Author |
Jun Shen, MD, Professor, Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou 510120, Guangdong Province, China. shenjun@mail.sysu.edu.cn |
| Key Words |
Liver failure; Radiomics; Gadoxetic acid; Magnetic resonance imaging; Hepatocellular carcinoma; |
| Core Tip |
Serological indexes, indocyanine green clearance rate at 15 min, liver volumetry, and clinical scoring systems are commonly used to determine liver function capacity and predict postoperative residual liver function. However, these indexes are not sufficiently accurate for predicting the risk of postoperative liver failure. We constructed a radiomics signature based on preoperative hepatobiliary phase gadoxetic acid-enhanced magnetic resonance imaging. This radiomics signature achieves favorable performance in predicting liver failure in cirrhotic patients with hepatocellular carcinoma after major hepatectomy. Incorporating indocyanine green clearance rate at 15 min into the radiomics signature further improves the predictive performance for postoperative liver failure. |
| Publish Date |
2020-03-21 02:52 |
| Citation |
Zhu WS, Shi SY, Yang ZH, Song C, Shen J. Radiomics model based on preoperative gadoxetic acid-enhanced MRI for predicting liver failure. World J Gastroenterol 2020; 26(11): 1208-1220 |
| URL |
https://www.wjgnet.com/1007-9327/full/v26/i11/1208.htm |
| DOI |
https://dx.doi.org/10.3748/wjg.v26.i11.1208 |
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